Improve bit Boilerplate RAG implementation (#11258)

src/Templates/Boilerplate/Bit.Boilerplate/.template.config/template.json

@@ -170,14 +170,14 @@
             "displayName": "Add aspire?",
             "type": "parameter",
             "datatype": "bool",
-            "defaultValue": "false",
+            "defaultValue": "true",
             "description": "Adds aspire"
         },
         "notification": {
             "displayName": "Add push notification?",
             "type": "parameter",
             "datatype": "bool",
-            "defaultValue": "false",
+            "defaultValue": "true",
             "description": "Adds push notification."
         },
         "sample": {
@@ -484,7 +484,8 @@
                         "src/Server/Boilerplate.Server.Api/Models/Todo/**",
                         "src/Server/Boilerplate.Server.Api/Data/Configurations/Todo/**",
                         "src/Shared/Controllers/Todo/**",
-                        "src/Client/Boilerplate.Client.Core/Components/Pages/TodoPage.*"
+                        "src/Client/Boilerplate.Client.Core/Components/Pages/TodoPage.*",
+                        "src/Client/Boilerplate.Client.Core/images/backgrounds/empty-todo-list-bg.svg"
                     ]
                 },
                 {

src/Templates/Boilerplate/Bit.Boilerplate/README.md

@@ -38,11 +38,11 @@ This project gets generated by bit-bp template v-9.11.3 using the following comm
         <!--#if (captcha == "reCaptcha")-->
             --captcha reCaptcha
         <!--#endif-->
-        <!--#if (aspire == true)-->
-            --aspire
+        <!--#if (aspire == false)-->
+            --aspire false
         <!--#endif-->
-        <!--#if (notification == true)-->
-            --notification
+        <!--#if (notification == false)-->
+            --notification false
         <!--#endif-->
         <!--#if (sample == true)-->
             --sample

src/Templates/Boilerplate/Bit.Boilerplate/src/Server/Boilerplate.Server.Api/Program.Services.cs

@@ -247,7 +247,7 @@ void AddDbContext(DbContextOptionsBuilder options)
             }
             options.UseSqlite(connectionStringBuilder.ConnectionString, dbOptions =>
             {
-
+                // dbOptions.UseQuerySplittingBehavior(QuerySplittingBehavior.SplitQuery);
             });
             //#endif
             //#if (IsInsideProjectTemplate == true)
@@ -260,18 +260,20 @@ void AddDbContext(DbContextOptionsBuilder options)
                 {
                     dbOptions.UseVectorSearch();
                 }
+                // dbOptions.UseQuerySplittingBehavior(QuerySplittingBehavior.SplitQuery);
             });
             //#elif (database == "PostgreSQL")
             var dataSourceBuilder = new Npgsql.NpgsqlDataSourceBuilder(configuration.GetConnectionString("PostgreSQLConnectionString"));
             dataSourceBuilder.EnableDynamicJson();
             options.UseNpgsql(dataSourceBuilder.Build(), dbOptions =>
             {
                 dbOptions.UseVector();
+                // dbOptions.UseQuerySplittingBehavior(QuerySplittingBehavior.SplitQuery);
             });
             //#elif (database == "MySql")
             options.UseMySql(configuration.GetConnectionString("MySqlConnectionString"), ServerVersion.AutoDetect(configuration.GetConnectionString("MySqlConnectionString")), dbOptions =>
             {
-
+                // dbOptions.UseQuerySplittingBehavior(QuerySplittingBehavior.SplitQuery);
             });
             //#elif (database == "Other")
             throw new NotImplementedException("Install and configure any database supported by ef core (https://learn.microsoft.com/en-us/ef/core/providers)");

src/Templates/Boilerplate/Bit.Boilerplate/src/Server/Boilerplate.Server.Api/Services/ProductEmbeddingService.cs

@@ -7,7 +7,17 @@
 namespace Boilerplate.Server.Api.Services;
 
 /// <summary>
-/// This class stores vectorized products and provides methods to query/manage them.
+/// Approaches to implement text search:
+/// 1- Simple string matching (e.g., `Contains` method).
+/// 2- Full-text search using database capabilities (e.g., PostgreSQL's full-text search).
+/// 3- Vector-based search using embeddings (e.g., using OpenAI's embeddings).
+/// This service implements vector-based search using embeddings that has the following advantages:
+///     - More accurate search results based on semantic meaning rather than just similarity matching.
+///     - Multi-language support, as embeddings can capture the meaning of words across different languages.
+/// And has the following disadvantages:
+///     - Requires additional processing to generate embeddings for the text.
+///     - Require more storage space for embeddings compared to simple text search.
+/// The simple full-text search would be enough for product search case, but we have implemented the vector-based search to demonstrate how to use embeddings in the project.
 /// </summary>
 public partial class ProductEmbeddingService
 {
@@ -20,7 +30,7 @@ public partial class ProductEmbeddingService
     public async Task<IQueryable<Product>> GetProductsBySearchQuery(string searchQuery, CancellationToken cancellationToken)
     {
         //#if (database != "PostgreSQL" && database != "SqlServer")
-        // The RAG has been implemented for PostgreSQL only. Check out https://github.com/bitfoundation/bitplatform/blob/develop/src/Templates/Boilerplate/Bit.Boilerplate/src/Server/Boilerplate.Server.Api/Services/ProductEmbeddingService.cs
+        // The RAG has been implemented for PostgreSQL / SQL Server only. Check out https://github.com/bitfoundation/bitplatform/blob/develop/src/Templates/Boilerplate/Bit.Boilerplate/src/Server/Boilerplate.Server.Api/Services/ProductEmbeddingService.cs
         return dbContext.Products.Where(p => p.Name!.Contains(searchQuery) || p.Category!.Name!.Contains(searchQuery));
         //#else
         var embeddedUserQuery = await EmbedText(searchQuery, cancellationToken);
@@ -60,7 +70,11 @@ public async Task Embed(Product product, CancellationToken cancellationToken)
         await dbContext.Entry(product).Reference(p => p.Category).LoadAsync(cancellationToken);
 
         // TODO: Needs to be improved.
-        var embedding = await EmbedText($"Name: {product.Name}, Manufacture: {product.Category!.Name}, Description: {product.DescriptionText} {product.PrimaryImageAltText}, Price: {product.Price}", cancellationToken);
+        var embedding = await EmbedText($@"
+Name: **{product.Name}**
+Manufacture: **{product.Category!.Name}**
+Description: {product.DescriptionText}
+Appearance: {product.PrimaryImageAltText}", cancellationToken);
 
         if (embedding.HasValue)
         {
@@ -89,6 +103,14 @@ public async Task Embed(Product product, CancellationToken cancellationToken)
         var embeddingGenerator = serviceProvider.GetService<IEmbeddingGenerator<string, Embedding<float>>>();
         if (embeddingGenerator is null)
             return env.IsDevelopment() ? null : throw new InvalidOperationException("Embedding generator is not registered.");
+
+        input = $@"
+Name: **{input}**
+Manufacture: **{input}**
+Description: {input}
+Appearance: {input}";
+
+
         var embedding = await embeddingGenerator.GenerateVectorAsync(input, options: new() { }, cancellationToken);
         return embedding.ToArray();
         //#endif

src/Templates/Boilerplate/Bit.Boilerplate/src/Server/Boilerplate.Server.Api/SignalR/AppHub.Chatbot.cs

@@ -95,7 +95,10 @@ async Task HandleIncomingMessage(string incomingMessage, CancellationToken messa
                                         .LogError("Chat reported issue: User email: {emailAddress}, Conversation history: {conversationHistory}", emailAddress, conversationHistory);
                                 }, name: "SaveUserEmailAndConversationHistory", description: "Saves the user's email address and the conversation history for future reference. Use this tool when the user provides their email address during the conversation. Parameters: emailAddress (string), conversationHistory (string)"),
                                 //#if (module == "Sales")
-                                AIFunctionFactory.Create(async ([Description("Concise summary of these user requirements in English Language")] string userNeeds, [Description("Car manufacturer's English name (Optional)")] string? manufacturer) =>
+                                AIFunctionFactory.Create(async ([Description("Concise summary of these user requirements")] string userNeeds,
+                                    [Description("Car manufacturer's name (Optional)")] string? manufacturer,
+                                    [Description("Car price below this value (Optional)")] decimal? maxPrice,
+                                    [Description("Car price above this value (Optional)")] decimal? minPrice) =>
                                 {
                                     if (messageSpecificCancellationToken.IsCancellationRequested)
                                         return null;
@@ -104,8 +107,10 @@ async Task HandleIncomingMessage(string incomingMessage, CancellationToken messa
                                     var productEmbeddingService = scope.ServiceProvider.GetRequiredService<ProductEmbeddingService>();
                                     var searchQuery = string.IsNullOrWhiteSpace(manufacturer)
                                         ? userNeeds
-                                        : $"{userNeeds}, Manufacturer: {manufacturer}";
+                                        : $"**{manufacturer}** {userNeeds}";
                                     var recommendedProducts = await (await productEmbeddingService.GetProductsBySearchQuery(searchQuery, messageSpecificCancellationToken))
+                                        .WhereIf(maxPrice.HasValue, p => p.Price <= maxPrice!.Value)
+                                        .WhereIf(minPrice.HasValue, p => p.Price >= minPrice!.Value)
                                         .Take(10)
                                         .Project()
                                         .Select(p => new